基于PDR和RSSI的室内定位算法研究

发布时间：2018-02-21 12:59

本文关键词： 室内定位系统 PDR算法接收信号强度指示动态路径衰减指数动态区间粒子滤波　出处：《仪器仪表学报》2015年05期 　论文类型：期刊论文

【摘要】：构建了基于无线传感网络的行人航迹推算(PDR)系统,通过RSSI定位为其提供绝对定位信息。在RSSI定位中,提出基于PDR方位信息的自适应Flip-Flop RSSI信息预处理机制和RSSI指纹信息融合动态路径衰减指数的定位算法,以改善RSSI定位算法的抗噪声干扰能力。在多信息融合粒子滤波环节中,针对传统算法中滤波精度与滤波实时性很难同时得到改善的问题,提出基于PDR信息与RSSI定位信息的动态区间粒子滤波算法,通过PDR方位信息自适应控制区间衍生粒子数量以提高滤波实时性,并将建筑地图信息、RSSI定位信息及其可信度因子融入粒子权值计算中以提高定位精度。经实验验证,提出的算法在RSSI定位抗噪声能力方面,以及融合定位精度和滤波实时性方面都取得了良好的效果,与传统算法相比最大定位误差由3.16 m降低到1.81 m,滤波时间也由7.21 s降至7.01 s。
[Abstract]:A pedestrian track estimation system based on wireless sensor network (WSN) is constructed, which provides absolute positioning information through RSSI positioning. In RSSI positioning, An adaptive Flip-Flop RSSI information preprocessing mechanism based on PDR azimuth information and a location algorithm based on dynamic path attenuation index of RSSI fingerprint information fusion are proposed to improve the anti-noise ability of RSSI location algorithm. Aiming at the problem that it is difficult to improve both the filtering accuracy and the real-time performance of the traditional algorithm, a dynamic interval particle filter algorithm based on PDR information and RSSI location information is proposed. Adaptive control of the number of interval derived particles based on PDR azimuth information is used to improve the real-time filtering, and the location information and its reliability factor of building map information are incorporated into the particle weight calculation to improve the positioning accuracy. The proposed algorithm has achieved good results in anti-noise capability of RSSI localization, fusion positioning accuracy and real-time filtering. Compared with the traditional algorithm, the maximum localization error is reduced from 3.16 m to 1.81 m, and the filtering time is also reduced from 7.21 s to 7.01 s.
【作者单位】：上海大学机电工程与自动化学院;
【分类号】：TN929.5;TP212.9

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